When performing geospatial analysis, data analysts often use various indices to provide an analytic or graphical analysis framework. One example of the use of indices occurs within precision agriculture. A Normalized Difference Vegetation Index (NDVI) may be used to represent healthy vegetation, where each NDVI data point includes a value between −1.0 (i.e., no vegetation) and +1.0 (i.e., healthy vegetation). However, data for many indices are concentrated within a narrow range. For example, NDVI values for a given agricultural field are often concentrated within the range of 0.7 to 0.8. What is needed is an improved analysis framework for index-based geospatial analysis.